Prospective: Computer Systems
Program Requirements
All EECS MEng students should expect to complete four (4) technical courses within the EECS department at the graduate level, the Fung Institute’s engineering leadership curriculum, as well as a capstone project that will be hosted by the EECS department. You must select a project from the list here.
Capstone Projects
The two-semester capstone experience will challenge you to integrate your technical and leadership skills to innovate in a dynamic, results-driven environment. Working with a team of fellow students, you will engineer solutions using cutting-edge technology and methods to address crucial industry, market, or societal needs. Capstone teams consist of three to five students. The size of each team is curated to optimize team dynamics and provide rich opportunity for developing effective leadership and teaming skills. There are two major project types: faculty projects and partner projects. Capstone matching and assignment takes place in the start of Fall semester. Projects vary from year to year, and there is no guaranteed placement until students have gone through the matching process.
Faculty Projects
Students working on faculty projects are advised by PhD candidates, post-doctoral researchers, and faculty from the UC Berkeley College of Engineering.
Partner Projects
Students working on partner projects are advised by a technical expert from a partnering organization.
Deliverables
Each Capstone team will have three types of deliverables:
- Technical deliverables are set in consultation with the advising team. These vary from project to project and may include: prototypes, experiments, data analyses, etc.
- Project management and teaming deliverables are shared by the MEng cohort. These include: project charter, project plan, stakeholder engagement strategy, etc.
- Reporting deliverables are shared by the MEng cohort. These include: final report, final presentation slidedeck, project brief, Capstone showcase, etc.
Technical Courses
At least THREE of your four technical courses should be chosen from the list below. The remaining technical courses should be chosen from your own or another MEng area of concentration within the EECS Department.
Typical Fall Semester Course Offerings —
- CS C200A, Principles & Techniques of Data Science
- CS 260A, User Interface Design and Development
- CS 260B, Human-Computer Interaction Research
- CS 261, Security in Computer Systems
- CS 262A, Advanced Topics in Computer Systems
- CS 265, Compiler Optimization and Code Generation
- CS 271, Randomness and Computation
- CS 276, Cryptography
- CS C281A, Statistical Learning Theory
- CS 282A, Designing, Visualizing and Understanding Deep Neural Networks
- CS 288, Natural Language Processing
- CS 289A, Introduction to Machine Learning
- EECS 227AT, Optimization Models in Engineering
- EECS 227BT, Convex Optimization
- EE 225D, Audio Signal Processing in Humans and Machines
- Related Special Topics (CS 294)
Typical Spring Semester Course Offerings —
- CS C200A, Principles & Techniques of Data Science
- CS 261, Security in Computer Systems
- CS 262A, Advanced Topics in Computer Systems
- CS 267, Parallel Computing
- CS 280, Computer Vision
- CS C281A. Statistical Learning Theory
- CS 282A, Designing, Visualizing and Understanding Deep Neural Networks
- CS 289A, Introduction to Machine Learning
- CS 285, Deep Reinforcement Learning, Decision Making, and Control
- EECS 227AT, Optimization Models in Engineering
- EE 225D, Audio Signal Processing in Humans and Machines
- EE 227BT, Convex Optimization
- Related Special Topics (CS 294)
Note: The courses listed here are not guaranteed to be offered, and the course schedule may change without notice. Refer to the UC Berkeley Course Schedule for further enrollment information.